An individualized nomogram for survival prediction in intrahepatic cholangiocarcinoma: a population-based analysis.
- 1School of Information Science and Engineering, Qilu Normal University, No. 2 Wenbo Road, Jinan, China.
- 2Department of Hepatobiliary Surgery, Jinan Central Hospital Affiliated to Shandong First Medical University, No. 105 Jiefang Road, Jinan, China. [email protected].
- 3Department of Hepatobiliary Surgery, Jinan Central Hospital Affiliated to Shandong First Medical University, No. 105 Jiefang Road, Jinan, China.
Abstract
Background
Intrahepatic cholangiocarcinoma (ICC) is an aggressive malignancy with poor prognosis. Current prognostic systems, including TNM staging system, incompletely incorporate important clinical and pathological factors. This study aims to develop and validate an individualized nomogram for predicting overall survival (OS) in ICC patients.Methods
A total of 1,751 ICC patients diagnosed between 2011 and 2021 were identified from the Surveillance, Epidemiology, and End Results (SEER) database for model development and internal validation. A temporally distinct SEER cohort of 751 ICC patients diagnosed between 2000 and 2010 was used for temporal validation. Twelve candidate predictors were prespecified, and the final nomogram variables were retained from the multivariable Cox model according to a predefined retention threshold. Model performance was evaluated using the concordance index (C-index), time-dependent area under the receiver operating characteristic curve (time-dependent AUC), calibration curves, decision curve analysis (DCA), and integrated discrimination improvement (IDI). Kaplan-Meier analysis was used for risk stratification.Results
The nomogram demonstrated good discriminative ability, with C-indices of 0.761 (training cohort) and 0.732 (validation cohort), and time-dependent AUC values ranging from 0.74 to 0.84 across 1-, 3-, and 5-year predictions. Calibration curves revealed good agreement between predicted and observed survival probabilities in both cohorts. The model outperformed the TNM staging system, with IDI values of 0.197, 0.393, and 0.238 for 1-, 3-, and 5-year predictions, respectively (all P < 0.001). DCA indicated greater net benefit across a range of threshold probabilities. Risk stratification significantly differentiated high-risk from low-risk patients (log-rank P < 0.001).Conclusion
The proposed nomogram provides individualized prediction of 1-, 3-, and 5-year OS in ICC patients and may assist in risk stratification and prognostic assessment.
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BibTeX
@article{xie2026individualized,
title = {{An individualized nomogram for survival prediction in intrahepatic cholangiocarcinoma: a population-based analysis.}},
author = {Hui Xie and Xiangyu Wang and Lingguang Shen and Fatao Hao and Yong Meng and Jianbin Du},
journal = {World journal of surgical oncology},
year = {2026},
month = jul,
doi = {10.1186/s12957-026-04509-x},
url = {https://europepmc.org/article/MED/42894228},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - An individualized nomogram for survival prediction in intrahepatic cholangiocarcinoma: a population-based analysis.
AU - Hui Xie
AU - Xiangyu Wang
AU - Lingguang Shen
AU - Fatao Hao
AU - Yong Meng
AU - Jianbin Du
PY - 2026
DA - 2026/07/01
JO - World journal of surgical oncology
DO - 10.1186/s12957-026-04509-x
UR - https://europepmc.org/article/MED/42894228
AB - Background Intrahepatic cholangiocarcinoma (ICC) is an aggressive malignancy with poor prognosis. Current prognostic systems, including TNM staging system, incompletely incorporate important clinical and pathological factors. This study aims to develop and validate an individualized nomogram for predicting overall survival (OS) in ICC patients.Methods A total of 1,751 ICC patients diagnosed between 2011 and 2021 were identified from the Surveillance, Epidemiology, and End Results (SEER) database for model development and internal validation. A temporally distinct SEER cohort of 751 ICC patients diagnosed between 2000 and 2010 was used for temporal validation. Twelve candidate predictors were prespecified, and the final nomogram variables were retained from the multivariable Cox model according to a predefined retention threshold. Model performance was evaluated using the concordance index (C-index), time-dependent area under the receiver operating characteristic curve (time-dependent AUC), calibration curves, decision curve analysis (DCA), and integrated discrimination improvement (IDI). Kaplan-Meier analysis was used for risk stratification.Results The nomogram demonstrated good discriminative ability, with C-indices of 0.761 (training cohort) and 0.732 (validation cohort), and time-dependent AUC values ranging from 0.74 to 0.84 across 1-, 3-, and 5-year predictions. Calibration curves revealed good agreement between predicted and observed survival probabilities in both cohorts. The model outperformed the TNM staging system, with IDI values of 0.197, 0.393, and 0.238 for 1-, 3-, and 5-year predictions, respectively (all P < 0.001). DCA indicated greater net benefit across a range of threshold probabilities. Risk stratification significantly differentiated high-risk from low-risk patients (log-rank P < 0.001).Conclusion The proposed nomogram provides individualized prediction of 1-, 3-, and 5-year OS in ICC patients and may assist in risk stratification and prognostic assessment.
SN - 1477-7819
ER -